Biography - Rafael A. Calvo

Building software applications that learn, and that help people learn.

PhD (Univ. Nacional de Rosario - Argentina, 2000)

Grad Cert in Higher Education (The University of Sydney, 2005)

Licenciado (Univ. Nacional de Rosario - Argentina, 1991),

Rafael Calvo is Associate Professor at the University of Sydney. He has a PhD in Artificial Intelligence applied to automatic document classification (e.g. web site classification). He has taught at several Universities, high schools and professional training institutions. He worked at the Language Technology Institute in Carnegie Mellon University, Universidad Nacional de Rosario (Argentina) and on sabbaticals at The University of Cambridge and University of Memphis. Rafael also has worked as an Internet consultant for projects in Australia, Brasil, the US and Argentina. Rafael is the recipient of 5 teaching awards, and the author of two books and many publications in the fields of learning technologies, affective computing and computational intelligence. Rafael is Associate Editor of the IEEE Transactions on Learning Technologies and of IEEE Transactions on Affective Computing and Senior Member of IEEE.

Dr Rafael Calvo’s contributions are centred around developing data mining algorithms and software architectures that integrate into real world applications. These applications are referred to as Intelligent Information Systems and he has created both web-based and mobile application systems.

His best example of developing new algorithms is a world-class pattern-recognition method for forecasting sunspots, a standard benchmark for time series forecasting that has important effects on weather and telecommunications. The research was based on a series of neural network algorithms that forecast the number of sunspots within a given period of time. The pattern-recognition method was later applied to other areas to successfully forecast monsoon rainfall in India. Monsoon rainfall has dramatic effects on the lives of more than a billion people living in the Indian subcontinent; improving the forecast of monsoon rainfall helps planning for flood emergencies and optimum crop yields.

Dr. Calvo has successfully applied novel machine learning techniques to other fields and built information systems that use them, particularly text mining. They include: a Naive Bayes and Neural Network that automatically classifies corporate announcements in the Capital Markets CRC; Naïve Bayes that classifies and redirects student assignments in mathForum.org and a mobile phone application for the Australian Biosecurity CRC that uses Naïve Bayes to produce probable diseases from a list of disease symptoms.

Dr. Calvo has also made significant contributions to the field of educational technologies. He introduced the concept of “e-learning frameworks”, bringing together the ideas of educational design patterns (i.e. scripts) with architectural abstractions used in software engineering. His research has provided increasing evidence of how student conceptions about learning tasks are related to the strategies and intent with which they approach these tasks which are in turn related to the learning outcomes. This student-centred research approach has been applied to several empirical studies around the development of learning technologies and to a new development methodology informed by the student experience.